python之Matplotlib Graphs下的渐变填充

我从these two posts on SO得到了很多信息关于在 matplotlib 中将渐变填充放在曲线下方。我尝试了同样的事情，在一个轴上绘制多个图，并按它们的顺序和它们的 alpha 来确保它们可见。我在 PIL 中遇到错误，此代码输出此图:

是否可以让绘图下方的“填充”进一步下降，并修复右下角的错误？我通过将原始数据放在 bpaste 上来包含我在这个例子中使用的数据，所以即使它很长，这个例子也是完全独立的。

会不会跟使用的后端有关系？

谢谢，贾里德

import pandas as pd 
import matplotlib.pyplot as plt 
import matplotlib.colors as mcolors 
from matplotlib.patches import Polygon 
from matplotlib.ticker import Formatter, FuncFormatter 
import matplotlib 
import numpy as np 
from PIL import Image 
from PIL import ImageDraw 
from PIL import ImageFilter 
 
 
df = pd.read_csv('https://bpaste.net/raw/87cbf69259ae') 
df = df.set_index('Date', drop=True) 
df.index = pd.to_datetime(df.index) 
 
 
df1 = pd.read_csv('https://bpaste.net/raw/bc06b26b0b8b') 
df1 = df1.set_index('Date', drop=True) 
df1.index = pd.to_datetime(df1.index) 
 
def zfunc(x, y, fill_color='k', alpha=1.0, xmin=None, xmax=None, ymin=None, ymax=None): 
 
    if xmax is not None: 
        xmax = int(xmax) 
 
    if xmin is not None: 
        xmin = int(xmin) 
 
    if ymax is not None: 
        ymax = int(ymax) 
 
    if ymin is not None: 
        ymin = int(ymin) 
 
    w, h = xmax-xmin, ymax-ymin 
    z = np.empty((h, w, 4), dtype=float) 
    rgb = mcolors.colorConverter.to_rgb(fill_color) 
    z[:,:,:3] = rgb 
 
    # Build a z-alpha array which is 1 near the line and 0 at the bottom. 
    img = Image.new('L', (w, h), 0) 
    draw = ImageDraw.Draw(img) 
 
    xy = (np.column_stack([x, y])) 
    xy -= xmin, ymin 
 
    # Draw a blurred line using PIL 
    draw.line(map(tuple, xy.tolist()), fill=255, width=15) 
    img = img.filter(ImageFilter.GaussianBlur(radius=25)) 
 
    # Convert the PIL image to an array 
    zalpha = np.asarray(img).astype(float)  
    zalpha *= alpha/zalpha.max() 
 
    # make the alphas melt to zero at the bottom 
    n = int(zalpha.shape[0] / 4) 
 
    zalpha[:n] *= np.linspace(0, 10, n)[:, None] 
    z[:,:,-1] = zalpha 
    return z 
 
 
def gradient_fill(x, y, fill_color=None, ax=None, ylabel=None, zfunc=None, **kwargs): 
 
    if ax is None: 
        ax = plt.gca() 
 
    if ylabel is not None: 
        ax.set_ylabel(ylabel, weight='bold', color='white') 
 
    class DateFormatter(Formatter): 
        def __init__(self, dates, fmt='%b \'%y'): 
            self.dates = dates 
            self.fmt = fmt 
 
        def __call__(self, x, pos=0): 
            'Return the label for time x at position pos' 
            ind = int(round(x)) 
            if ind>=len(self.dates) or ind<0: return '' 
 
            return self.dates[ind].strftime(self.fmt) 
 
    def millions(x, pos): 
        return '$%d' % x 
 
    dollar_formatter = FuncFormatter(millions)      
    formatter = DateFormatter(df.index) 
    ax.yaxis.grid(linestyle='-', alpha=0.5, color='white', zorder=-1)  
 
    line, = ax.plot(x, y, linewidth=2.0, c=fill_color, **kwargs) 
 
    if fill_color is None: 
        fill_color = line.get_color() 
 
    zorder = line.get_zorder() 
    if 'alpha' in kwargs: 
        alpha = kwargs['alpha'] 
    else: 
        alpha = line.get_alpha() 
        alpha = 1.0 if alpha is None else alpha 
 
    xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max() 
    diff = ymax - ymin 
    ymin = ymin - diff*0.15 
    ymax = diff*0.05 + ymax 
 
    if zfunc is None: 
        ## Grab an array of length (cols,rows,spacing) but don't initialize values 
        z = np.empty((110, 1, 4), dtype=float) 
        ## get color to fill for current axix line 
        rgb = mcolors.colorConverter.to_rgb(fill_color) 
        z[:,:,:3] = rgb 
        z[:,:,-1] = np.linspace(0, alpha, 110)[:,None] 
    else: 
        z = zfunc(x, y, fill_color=fill_color, alpha=alpha, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax) 
 
    im = ax.imshow(z, aspect='auto', extent=[xmin, xmax, ymin, ymax], origin='lower', zorder=zorder) 
 
    xy = np.column_stack([x, y]) 
    xy = np.vstack([[xmin, ymin], xy, [xmax, ymin], [xmin, ymin]]) 
    clip_path = Polygon(xy, facecolor='none', edgecolor='none', closed=True) 
    ax.add_patch(clip_path) 
    ax.patch.set_facecolor('black') 
    im.set_clip_path(clip_path) 
 
 
    ax.xaxis.set_major_formatter(formatter) 
    ax.yaxis.set_major_formatter(dollar_formatter) 
 
    for tick in ax.get_yticklabels(): 
        tick.set_color('white') 
 
    for tick in ax.get_xticklabels(): 
        tick.set_color('white') 
 
    w = 17.5 * 1.5  # approximate size in inches of 1280 
    h = 7.5 * 1.5  # approximate size in inches of 720 
    fig =  plt.gcf() 
    fig.set_size_inches(w, h) 
#     fig.autofmt_xdate() 
    plt.rcParams['xtick.major.pad']='20' 
    matplotlib.rcParams['ytick.major.pad']='20' 
    matplotlib.rcParams.update({'font.size': 22}) 
 
    ax.set_ylim((ymin, ymax)) 
    #ax.autoscale(True) 
    return line, im, ax 
 
line, im, ax = gradient_fill(np.arange(len(df1.index)), df1['/CL_Close'], fill_color='#fdbf6f', ylabel='Crude Oil', alpha=1.0, zfunc=zfunc) 
ax2 = ax.twinx() 
gradient_fill(np.arange(len(df.index)), df['/ES_Close'], ax=ax2, fill_color='#cab2d6', ylabel='S&P', alpha=0.75, zfunc=zfunc) 
ax2.yaxis.grid(False) 

请您参考如下方法:

问题出在您的 zfunc 中。 您说您想通过将 alpha 与 np.linspace(0,10,n) 相乘来将它们淡化为零。

尝试:

zalpha[:n] *= np.linspace(0, 1, n)[:, None] 

那么它对我有用...